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https://issues.apache.org/jira/browse/SPARK-4352?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14572323#comment-14572323
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Saisai Shao commented on SPARK-4352:
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Hi Sandy, Thanks a lot for pointing out. So consider this situation, we have 20
tasks with no locality preference, 10 tasks with <a, b, d>, also we have 18
executors with 2 cores per executor, so based on your description, we will
request:
5 container requests on <a, b, d>
12 container requests with no locality preference.
But I think is it better for such allocation:
15 container requests on <a, b, d>
3 container requests with no locality preference.
Besides I think {{task number <= executor number * cores}} will be ideally
avoided by ExecutorAllocationManager, ideally only 15 executors is enough, but
currently request 3 more executors. Sorry for any misunderstanding :).
> Incorporate locality preferences in dynamic allocation requests
> ---------------------------------------------------------------
>
> Key: SPARK-4352
> URL: https://issues.apache.org/jira/browse/SPARK-4352
> Project: Spark
> Issue Type: Improvement
> Components: Spark Core, YARN
> Affects Versions: 1.2.0
> Reporter: Sandy Ryza
> Assignee: Saisai Shao
> Priority: Critical
> Attachments: Supportpreferrednodelocationindynamicallocation.pdf
>
>
> Currently, achieving data locality in Spark is difficult unless an
> application takes resources on every node in the cluster.
> preferredNodeLocalityData provides a sort of hacky workaround that has been
> broken since 1.0.
> With dynamic executor allocation, Spark requests executors in response to
> demand from the application. When this occurs, it would be useful to look at
> the pending tasks and communicate their location preferences to the cluster
> resource manager.
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